First of all, the images needs to be converted to tensors. The first approach would be to create a tensor containing all the features (respectively a tensor containing all the labels). This should the way to go only if the dataset contains few images. const imageBuffer = await fs.readFile(feature_file); tensorFeature = tfnode.node.decodeImage(imageBuffer) // create a … Read more
jsdom Doesn’t seem to have TextEncoder defined in global for the DOM. So you can fill it in with the node.js one. test/custom-test-env.js: const Environment = require(‘jest-environment-jsdom’); /** * A custom environment to set the TextEncoder that is required by TensorFlow.js. */ module.exports = class CustomTestEnvironment extends Environment { async setup() { await super.setup(); if … Read more
The speeds are different: Tensorflow > tfjs > brainjs. Python can be directly compiled to machine code and directly use the CPU and GPU, whereas tfjs is a script-language which is being compiled on the client and has to use the <canvas> in the browser to access the GPU the same as brain.js (I am … Read more
This worked for me: Go to Inspect → Settings (Symbol) gear → Uncheck Enable JavaScript source maps and Enable CSS source map. Refresh. (Note: Deactivate Adblock if the above process did not work.)